This package provides a collection of personal functions designed to simplify and streamline common R programming tasks. This package provides reusable tools and shortcuts for frequently used calculations and workflows.

Supports calculations and visualization for renewable power systems and the environment. Analysis and graphical tools for DC and AC circuits and their use in electric power systems. Analysis and graphical tools for thermodynamic cycles and heat engines, supporting efficiency calculations in coal-fired power plants, gas-fired power plants. Calculations of carbon emissions and atmospheric CO2 dynamics. Analysis of power flow and demand for the grid, as well as power models for microgrids and off-grid systems. Provides resource and power generation for hydro power, wind power, and solar power.

Visualize your favorite XKCD comic strip directly from R. XKCD <https://xkcd.com> web comic content is provided under the Creative Commons Attribution-NonCommercial 2.5 License.

Import REDATAM formats into R via the Open REDATAM C++ library. The full context of this project and details about the implementation are available in <doi:10.1017/dap.2025.4> (Open Access).

This package provides a programmatic interface to the Web Service methods provided by the Global Biodiversity Information Facility (GBIF; <https://www.gbif.org/developer/summary>). GBIF is a database of species occurrence records from sources all over the globe. rgbif includes functions for searching for taxonomic names, retrieving information on data providers, getting species occurrence records, getting counts of occurrence records, and using the GBIF tile map service to make rasters summarizing huge amounts of data.

Rcpp bindings to the native C++ implementation of MS Numpress, that provides two compression schemes for numeric data from mass spectrometers. The library provides implementations of 3 different algorithms, 1 designed to compress first order smooth data like retention time or M/Z arrays, and 2 for compressing non smooth data with lower requirements on precision like ion count arrays. Refer to the publication (Teleman et al., (2014) <doi:10.1074/mcp.O114.037879>) for more details.

Facilitates efficient polygon search using kd trees. Coordinate level spatial data can be aggregated to higher geographical identities like census blocks, ZIP codes or police district boundaries. This process requires mapping each point in the given data set to a particular identity of the desired geographical hierarchy. Unless efficient data structures are used, this can be a daunting task. The operation point.in.polygon() from the package sp is computationally expensive. Here, we exploit kd-trees as efficient nearest neighbor search algorithm to dramatically reduce the effective number of polygons being searched.

This package provides a collection of methods for the robust analysis of univariate and multivariate functional data, possibly in high-dimensional cases, and hence with attention to computational efficiency and simplicity of use. See the R Journal publication of Ieva et al. (2019) <doi:10.32614/RJ-2019-032> for an in-depth presentation of the roahd package. See Aleman-Gomez et al. (2021) <arXiv:2103.08874> for details about the concept of depthgram.

We provide several avenues to predict and account for user-based mortality and tag loss during mark-recapture studies. When planning a study on a target species, the retentionmort_generation() function can be used to produce multiple synthetic mark-recapture datasets to anticipate the error associated with a planned field study to guide method development to reduce error. Similarly, if field data was already collected, the retentionmort() function can be used to predict the error from already generated data to adjust for user-based mortality and tag loss. The test_dataset_retentionmort() function will provide an example dataset of how data should be inputted into the function to run properly. Lastly, the retentionmort_figure() function can be used on any dataset generated from either model function to produce an rmarkdown printout of preliminary analysis associated with the model, including summary statistics and figures. Methods and results pertaining to the formation of this package can be found in McCutcheon et al. (in review, "Predicting tagging-related mortality and tag loss during mark-recapture studies").

This package provides a modified implementation of stepwise regression that greedily searches the space of interactions among features in order to build polynomial regression models. Furthermore, the hypothesis tests conducted are valid-post model selection due to the use of a revisiting procedure that implements an alpha-investing rule. As a result, the set of rejected sequential hypotheses is proven to control the marginal false discover rate. When not searching for polynomials, the package provides a statistically valid algorithm to run and terminate stepwise regression. For more information, see Johnson, Stine, and Foster (2019) <arXiv:1510.06322>.

This package contains tools for reading and writing data from or to files in the formats: akterm, dmna, Scintec Format-1, and Campbell Scientific TOA5.

An interface between the GRASS geographical information system ('GIS') and R', based on starting R from within the GRASS GIS environment, or running a free-standing R session in a temporary GRASS location; the package provides facilities for using all GRASS commands from the R command line. The original interface package for GRASS 5 (2000-2010) is described in Bivand (2000) <doi:10.1016/S0098-3004(00)00057-1> and Bivand (2001) <https://www.r-project.org/conferences/DSC-2001/Proceedings/Bivand.pdf>. This was succeeded by spgrass6 for GRASS 6 (2006-2016) and rgrass7 for GRASS 7 (2015-present). The rgrass package modernizes the interface for GRASS 8 while still permitting the use of GRASS 7'.

Determine the number of dimensions to retain in exploratory factor analysis. The main function, nest(), returns the solution and the plot(nest()) returns a plot.

Processing logical operations such as AND/OR/NOT operations dynamically. It also handles nesting in the operations.

Providing the container for the DockerParallel package.

Reproducibility is essential to the progress of research, yet achieving it remains elusive even in computational fields. Continuous Integration (CI) platforms offer a powerful way to launch automated workflows to check and document code, but often require considerable time, effort, and technical expertise to setup. We therefore developed the rworkflows suite to make robust CI workflows easy and freely accessible to all R package developers. rworkflows consists of 1) a CRAN/Bioconductor-compatible R package template, 2) an R package to quickly implement a standardised workflow, and 3) a centrally maintained GitHub Action.

Communications simulation package supporting forward error correction.

Application of reinsurance treaties to claims portfolios. The package creates a class Claims whose objective is to store claims and premiums, on which different treaties can be applied. A statistical analysis can then be applied to measure the impact of reinsurance, producing a table or graphical output. This package can be used for estimating the impact of reinsurance on several portfolios or for pricing treaties through statistical analysis. Documentation for the implemented methods can be found in "Reinsurance: Actuarial and Statistical Aspects" by Hansjöerg Albrecher, Jan Beirlant, Jozef L. Teugels (2017, ISBN: 978-0-470-77268-3) and "REINSURANCE: A Basic Guide to Facultative and Treaty Reinsurance" by Munich Re (2010) <https://www.munichre.com/site/mram/get/documents_E96160999/mram/assetpool.mr_america/PDFs/3_Publications/reinsurance_basic_guide.pdf>.

This package provides a collection of functions to simulate luminescence signals in quartz and Al2O3 based on published models.

Flux (mass per unit time) and Load (mass) are computed from timeseries estimates of analyte concentration and discharge. Concentration timeseries are computed from regression between surrogate and user-provided analyte. Uncertainty in calculations is estimated using bootstrap resampling. Code for the processing of acoustic backscatter from horizontally profiling acoustic Doppler current profilers is provided. All methods detailed in Livsey et al (2020) <doi:10.1007/s12237-020-00734-z>, Livsey et al (2023) <doi:10.1029/2022WR033982>, and references therein.

Set of tools to manipulate the JDemetra+ workspaces. Based on the RJDemetra package (which interfaces with version 2 of the JDemetra+ (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System (ESS) and the European System of Central Banks). This package provides access to additional workspace manipulation functions such as metadata manipulation, raw paths and wrangling of several workspaces simultaneously. These additional functionalities are useful as part of a CVS data production chain.

The mixed integer programming library MIPLIB (see <http://miplib.zib.de/>) is commonly used to compare the performance of mixed integer optimization solvers. This package provides functions to access MIPLIB from the R Optimization Infrastructure ('ROI'). More information about MIPLIB can be found in the paper by Koch et al. available at <http://mpc.zib.de/index.php/MPC/article/viewFile/56/28>. The README.md file illustrates how to use this package.

The Diceware method can be used to generate strong passphrases. In short, you roll a 6-faced dice 5 times in a row, the number obtained is matched against a dictionary of easily remembered words. By combining together 7 words thus generated, you obtain a password that is relatively easy to remember, but would take several millions years (on average) for a powerful computer to guess.

This package provides functions to reconstruct sessions from web log or other user trace data and calculate various metrics around them, producing tabular, output that is compatible with dplyr or data.table centered processes.